Transient stability enhancement of a gridconnected wind farm using an adaptive neurofuzzy controlled-flywheel energy storage system

With the rapid growth of the wind energy systems in the past years and their interconnection with the existing power system networks, it has become very significant to analyse and enhance the transient stability of the wind energy conversion systems connected to the grid. This study investigates the transient stability enhancement of a grid-connected wind farm using doubly-fed induction machine-based flywheel energy storage system. A cascaded adaptive neuro-fuzzy controller (ANFC) is introduced to control the insulated gate bipolar transistor switches-based frequency converter to enhance the transient stability of the grid-connected wind farm. The performance of the proposed control strategy is analysed under a severe symmetrical fault condition on both a single-machine infinite bus model and the IEEE-39 bus New England test system. The transient performance of the system is investigated by comparing the results of the system using the proposed ANFCs with that of the black-box optimisation technique-based proportional-integral controllers. The validity of the system is verified by the simulation results which are carried out using PSCAD/EMTDC environment

Simulation and Practical Implementation of ANFIS-Based MPPT Method for PV Applications Using Isolated Ćuk Converter

Photovoltaic (PV) module behavior is not linear in nature with respect to environmental conditions and hence exhibits nonlinear PV curves. There is only a single point in the nonlinear PV curve at which the power is maximum. Therefore, special methods have been proposed to track this maximum power point (MPP). This paper proposed an intelligent method for MPP tracking (MPPT) based on adaptive neuro-fuzzy inference system (ANFIS) controller. The proposed system consists of a PV module connected to a DC-DC isolated Ćuk converter and load. A MATLAB/SIMULINK-based MPPT model is built to test the behavior of the proposed method. The proposed method is tested under different weather scenarios. Simulation results exhibit the successful tracking of the proposed method under all ambient conditions. Comparison of the tracking behavior of the proposed method with the perturb and observe method is also presented in the simulation results. In addition, a 220 W prototype with the help of dSPACE 1104 data acquisition system is built and tested under practical weather conditions on a sunny day as well as on a cloudy day. Experimental results are presented to verify the effectiveness of the proposed method. These results exhibit satisfactory performance under different practical weather conditions

Magnetization-Dependent Core-Loss Model in a Three-Phase Self-Excited Induction Generator

Steady-state, transient, as well as dynamic analyses of self-excited induction generators (SEIGs) are generally well-documented. However, in most of the documented studies, core losses have been neglected or inaccurately modeled. This paper is concerned with the accurate modeling of core losses in SEIG analysis. The core loss is presented as a function related to the level of saturation. This relation is determined experimentally and integrated into a nonlinear model of the SEIG. The nonlinear model is solved using a mathematical optimization scheme to obtain the performance parameters of the SEIG. A new set of curves describing accurate behavior of the SEIG parameters is produced and presented in this paper. The computed parameters of the model are validated experimentally, and the agreement attained demonstrates the functionality and accuracy of the proposed core-loss model

Cascaded H-Bridge MLI and Three-Phase Cascaded VSI Topologies for Grid-Connected PV Systems with Distributed MPPT

Cascaded multilevel inverter topologies have received a great deal of attention for grid-connected PV systems. In this paper, three-cascaded multilevel inverter configurations are proposed for grid-connected PV applications. These are the three-phase cascaded H-bridge multilevel inverter topology, three-phase cascaded voltage-source inverter topology using inductors, and three-phase cascaded voltage-source inverter topology using coupled transformers. Distributed maximum power point tracking (MPPT) of PV modules using perturbation and observation algorithm is used for all presented topologies. In all presented configurations, each PV module is connected to one DC-DC isolated Ćuk converter for best MPPT achievement. Simulation is achieved by using the SIMULINK environment. The simulation results show that the three proposed topologies function well in improving the grid’s power quality. The grid currents are kept in phase with the grid voltage to ensure unity power factor, and the THD of the grid currents are within the acceptable range. The proposed topologies are experimentally implemented in the lab, and the switching pulses are generated with the help of the MicroLabBox data acquisition system. Comparing the three topologies according to the number of switches, voltage, and current stresses on switches and THD of the generated voltages and grid currents and according to the efficiency has been achieved in this paper, both experimentally and by simulation. The simulation and experimental results and comparisons are presented to verify the proposed topologies’ effectiveness and reliability

IoT-Based Hybrid Renewable Energy System for Smart Campus

There is a growing interest in increasing the penetration rate of renewable energy systems due to the drawbacks associated with the use of fossil fuels. However, the grid integration of renewable energy systems represents many challenging tasks for system operation, stability, reliability, and power quality. Small hybrid renewable energy systems (HRES) are small-scale power systems consisting of energy sources and storage units to manage and optimize energy production and consumption. Appropriate real-time monitoring of HRES plays an essential role in providing accurate information to enable the system operator to evaluate the overall performance and identify any abnormal conditions. This work proposes an internet of things (IoT) based architecture for HRES, consisting of a wind turbine, a photovoltaic system, a battery storage system, and a diesel generator. The proposed architecture is divided into four layers: namely power, data acquisition, communication network, and application layers. Due to various communication technologies and the missing of a standard communication model for HRES, this work, also, defines communication models for HRES based on the IEC 61850 standard. The monitoring parameters are classified into different categories, including electrical, status, and environmental information. The network modeling and simulation of a university campus is considered as a case study, and critical parameters, such as network topology, link capacity, and latency, are investigated and discussed